The generation and subtraction of sensory expectations within cerebellum-like structures

Does pre-speech auditory modulation reflect processes related to feedback monitoring or speech movement planning?

Previous studies have revealed that auditory processing is modulated during the planning phase immediately prior to speech onset. To date, the functional relevance of this pre-speech auditory modulation (PSAM) remains unknown. Here, we investigated whether PSAM reflects neuronal processes that are associated with preparing auditory cortex for optimized feedback monitoring as reflected in online speech corrections. Combining electroencephalographic PSAM data from a previous data set with new acoustic measures of the same participants' speech, we asked whether individual speakers' extent of PSAM is correlated with the implementation of within-vowel articulatory adjustments during /b/-vowel-/d/ word productions. Online articulatory adjustments were quantified as the extent of change in inter-trial formant variability from vowel onset to vowel midpoint (a phenomenon known as centering). This approach allowed us to also consider inter-trial variability in formant production, and its possible relation to PSAM, at vowel onset and midpoint separately. Results showed that inter-trial formant variability was significantly smaller at vowel midpoint than at vowel onset. PSAM was not significantly correlated with this amount of change in variability as an index of within-vowel adjustments. Surprisingly, PSAM was negatively correlated with inter-trial formant variability not only in the middle but also at the very onset of the vowels. Thus, speakers with more PSAM produced formants that were already less variable at vowel onset. Findings suggest that PSAM may reflect processes that influence speech acoustics as early as vowel onset and, thus, that are directly involved in motor command preparation (feedforward control) rather than output monitoring (feedback control).

Packet information encoding in a cerebellum-like circuit

Packet information encoding of neural signals was proposed for vision about 50 years ago and has recently been revived as a plausible strategy generalizable to natural and artificial sensory systems. It involves discrete image segmentation controlled by feedback and the ability to store and compare packets of information. This article shows that neurons of the cerebellum-like electrosensory lobe (EL) of the electric fish Gymnotus omarorum use spike-count and spike-timing distribution as constitutive variables of packets of information that encode one-by-one the electrosensory images generated by a self-timed series of electric organ discharges (EODs). To evaluate this hypothesis, extracellular unitary activity was recorded from the centro-medial map of the EL. Units recorded in high-decerebrate preparations were classified into six types using hierarchical cluster analysis of post-EOD spiking histograms. Cross-correlation analysis indicated that each EOD strongly influences the unit firing probability within the next inter-EOD interval. Units of the same type were similarly located in the laminar organization of the EL and showed similar stimulus-specific changes in spike count and spike timing after the EOD when a metal object was moved close by, along the fish's body parallel to the skin, or when the longitudinal impedance of a static cylindrical probe placed at the center of the receptive field was incremented in a stepwise manner in repetitive trials. These last experiments showed that spike-counts and the relative entropy, expressing a comparative measure of information before and after the step, were systematically increased with respect to a control in all unit types. The post-EOD spike-timing probability distribution and the relatively independent contribution of spike-timing and number to the content of information in the transmitted packet suggest that these are the constitutive image-encoding variables of the packets. Comparative analysis suggests that packet information transmission is a general principle for processing superposition images in cerebellum-like networks.

Does pre-speech auditory modulation reflect processes related to feedback monitoring or speech movement planning?

Previous studies have revealed that auditory processing is modulated during the planning phase immediately prior to speech onset. To date, the functional relevance of this pre-speech auditory modulation (PSAM) remains unknown. Here, we investigated whether PSAM reflects neuronal processes that are associated with preparing auditory cortex for optimized feedback monitoring as reflected in online speech corrections. Combining electroencephalographic PSAM data from a previous data set with new acoustic measures of the same participants' speech, we asked whether individual speakers' extent of PSAM is correlated with the implementation of within-vowel articulatory adjustments during /b/-vowel-/d/ word productions. Online articulatory adjustments were quantified as the extent of change in inter-trial formant variability from vowel onset to vowel midpoint (a phenomenon known as centering). This approach allowed us to also consider inter-trial variability in formant production and its possible relation to PSAM at vowel onset and midpoint separately. Results showed that inter-trial formant variability was significantly smaller at vowel midpoint than at vowel onset. PSAM was not significantly correlated with this amount of change in variability as an index of within-vowel adjustments. Surprisingly, PSAM was negatively correlated with inter-trial formant variability not only in the middle but also at the very onset of the vowels. Thus, speakers with more PSAM produced formants that were already less variable at vowel onset. Findings suggest that PSAM may reflect processes that influence speech acoustics as early as vowel onset and, thus, that are directly involved in motor command preparation (feedforward control) rather than output monitoring (feedback control).

Sensorimotor adaptation to destabilizing dynamics in weakly electric fish

Humans and other animals can readily learn to compensate for changes in the dynamics of movement. Such changes can result from an injury or changes in the weight of carried objects. These changes in dynamics can lead not only to reduced performance but also to dramatic instabilities. We evaluated the impacts of compensatory changes in control policies in relation to stability and robustness in Eigenmannia virescens, a species of weakly electric fish. We discovered that these fish retune their sensorimotor control system in response to experimentally generated destabilizing dynamics. Specifically, we used an augmented reality system to manipulate sensory feedback during an image stabilization task in which a fish maintained its position within a refuge. The augmented reality system measured the fish's movements in real time. These movements were passed through a high-pass filter and multiplied by a gain factor before being fed back to the refuge motion. We adjusted the gain factor to gradually destabilize the fish's sensorimotor loop. The fish retuned their sensorimotor control system to compensate for the experimentally induced destabilizing dynamics. This retuning was partially maintained when the augmented reality feedback was abruptly removed. The compensatory changes in sensorimotor control improved tracking performance as well as control-theoretic measures of robustness, including reduced sensitivity to disturbances and improved phase margins.

Role of the Cerebellum in the Construction of Functional and Geometrical Spaces

The perceptual and motor systems appear to have a set of movement primitives that exhibit certain geometric and kinematic invariances. Complex patterns and mental representations can be produced by (re)combining some simple motor elements in various ways using basic operations, transformations, and respecting a set of laws referred to as kinematic laws of motion. For example, point-to-point hand movements are characterized by straight hand paths with single-peaked-bell-shaped velocity profiles, whereas hand speed profiles for curved trajectories are often irregular and more variable, with speed valleys and inflections extrema occurring at the peak curvature. Curvature and speed are generically related by the 2/3 power law. Mathematically, such laws can be deduced from a combination of Euclidean, affine, and equi-affine geometries, whose neural correlates have been partially detected in various brain areas including the cerebellum and the basal ganglia. The cerebellum has been found to play an important role in the control of coordination, balance, posture, and timing over the past years. It is also assumed that the cerebellum computes forward internal models in relationship with specific cortical and subcortical brain regions but its motor relationship with the perceptual space is unclear. A renewed interest in the geometrical and spatial role of the cerebellum may enable a better understanding of its specific contribution to the action-perception loop and behavior's adaptation. In this sense, we complete this overview with an innovative theoretical framework that describes a possible implementation and selection by the cerebellum of geometries adhering to different mathematical laws.

Roles for cerebellum and subsumption architecture in central pattern generation

Within vertebrates, central pattern generators drive rhythmical behaviours, such as locomotion and ventilation. Their pattern generation is also influenced by sensory input and various forms of neuromodulation. These capabilities arose early in vertebrate evolution, preceding the evolution of the cerebellum in jawed vertebrates. This later evolution of the cerebellum is suggestive of subsumption architecture that adds functionality to a pre-existing network. From a central-pattern-generator perspective, what additional functionality might the cerebellum provide? The suggestion is that the adaptive filter capabilities of the cerebellum may be able to use error learning to appropriately repurpose pattern output. Examples may include head and eye stabilization during locomotion, song learning, and context-dependent alternation between learnt motor-control sequences.

So many toadfish, so little timea)

The oyster toadfish, Opsanus tau, has been a valuable biomedical model for a wide diversity of studies. However, its vocalization ability arguably has attracted the most attention, with numerous studies focusing on its ecology, behavior, and neurophysiology in regard to its sound production and reception. This paper reviews 30 years of research in my laboratory using this model to understand how aquatic animals detect, integrate, and respond to external environment cues. The dual vestibular and auditory role of the utricle is examined, and its ability to integrate multimodal input is discussed. Several suggestions for future research are provided, including in situ auditory recording, interjecting natural relevant ambient soundscapes into laboratory sound studies, adding transparency to the field of acoustic deterrents, and calls for fish bioacoustics teaching modules to be incorporated in K-12 curricula to excite and diversify the next generation of scientists.

Anatomical adventures in the fish auditory medullaa)

This paper provides an overview of my work on the central auditory system of fish. It focuses on my comparative analyses of a nucleus that receives input from the inner ear, the descending nucleus, and more specifically on that part of the descending nucleus supplied by the otolith end organs, the dorsal descending nucleus. I begin by summarizing my initial work on the bowfin, Amia calva, and go on to explain the importance of taking a comparative approach to understanding ancestral and specialized anatomical and putative functional characteristics of the dorsal descending nucleus in modern bony fishes, the teleosts.

Living life with an electric touch

The electric organ discharges (EODs) produced by weakly electric fish have long been a source of scientific intrigue and inspiration. The study of these species has contributed to our understanding of the organization of fixed action patterns, as well as enriching general imaging theory by unveiling the dual impact of an agent's actions on the environment and its own sensory system during the imaging process. This Centenary Review firstly compares how weakly electric fish generate species- and sex-specific stereotyped electric fields by considering: (1) peripheral mechanisms, including the geometry, channel repertoire and innervation of the electrogenic units; (2) the organization of the electric organs (EOs); and (3) neural coordination mechanisms. Secondly, the Review discusses the threefold function of the fish-centered electric fields: (1) to generate electric signals that encode the material, geometry and distance of nearby objects, serving as a short-range sensory modality or 'electric touch'; (2) to mark emitter identity and location; and (3) to convey social messages encoded in stereotypical modulations of the electric field that might be considered as species-specific communication symbols. Finally, this Review considers a range of potential research directions that are likely to be productive in the future.

An internal model for canceling self-generated sensory input in freely behaving electric fish

Internal models that predict the sensory consequences of motor actions are vital for sensory, motor, and cognitive functions. However, the relationship between motor action and sensory input is complex, often varying from one moment to another depending on the state of the animal and the environment. The neural mechanisms for generating predictions under such challenging, real-world conditions remain largely unknown. Using novel methods for underwater neural recording, a quantitative analysis of unconstrained behavior, and computational modeling, we provide evidence for an unexpectedly sophisticated internal model at the first stage of active electrosensory processing in mormyrid fish. Closed-loop manipulations reveal that electrosensory lobe neurons are capable of simultaneously learning and storing multiple predictions of the sensory consequences of motor commands specific to different sensory states. These results provide mechanistic insights into how internal motor signals and information about the sensory environment are combined within a cerebellum-like circuitry to predict the sensory consequences of natural behavior.

A mechanism for differential control of axonal and dendritic spiking underlying learning in a cerebellum-like circuit

In addition to the action potentials used for axonal signaling, many neurons generate dendritic "spikes" associated with synaptic plasticity. However, in order to control both plasticity and signaling, synaptic inputs must be able to differentially modulate the firing of these two spike types. Here, we investigate this issue in the electrosensory lobe (ELL) of weakly electric mormyrid fish, where separate control over axonal and dendritic spikes is essential for the transmission of learned predictive signals from inhibitory interneurons to the output stage of the circuit. Through a combination of experimental and modeling studies, we uncover a novel mechanism by which sensory input selectively modulates the rate of dendritic spiking by adjusting the amplitude of backpropagating axonal action potentials. Interestingly, this mechanism does not require spatially segregated synaptic inputs or dendritic compartmentalization but relies instead on an electrotonically distant spike initiation site in the axon-a common biophysical feature of neurons.

A simple model of the electrosensory electromotor loop in Gymnotus omarorum

This article introduces and tests a simple model that describes a neural network found in nature, the electrosensory control of an electromotor pacemaker. The cornerstone of the model is an early-stage filter based on the subtraction of a feedforward integrated version of the recent sensory past from the present input signal. The output of this filter governs the modulation of a premotor pacemaker command driving the sensory signal carrier generation and, in consequence, the timing of subsequent electrosensory input. This early filter has a biological parallel in the known connectivity of the first electrosensory relay within the brain stem of the weakly electric fish Gymnotus omarorum. Our biomimetic model of this active, perception-driven action-sensation cycle was contrasted with previously published and here provided new data. When the amplitude of the electrosensory input was manipulated to mimic previous experiments on the novelty detection characteristics, the model reproduces them rather faithfully. In addition, when we applied continuous variations to the input it shows that increases in stimulus amplitudes are followed by increases in the EOD rate, but decreases do not cause rate modulation suggesting a rectification in some stage of the loop. These behavioral experiments confirmed results generated the simulations suggesting that beyond explaining the novelty detection process this simple model is a good description of the electrosensory -electromotor loop in pulse weakly electric fish.

Getting the news in milliseconds: The role of early novelty detection in active electrosensory exploration

The pulse emitting weakly electric fish Gymnotus omarorum shows stereotyped "novelty responses" consisting of a transient acceleration of the rhythm of a self-emitted electric organ discharge that carries electrosensory signals. Here we show that rapid increases in electric image amplitude cause a "novelty detection potential" in the first electrosensory relay. This sign precedes and its amplitude predicts, the amplitude of the subsequent behavioral novelty response. Current source density analyses indicates its origin ar the layers of the electrosensory lobe where the main output neurons occur. Two types of units, referred to as "ON" and "OFF". Were recorded there in decerebrated fish. Firing probability of "OFF" units drastically decreased after a stepwise increase in electric image. By contrast, the very first novel stimuli after the increase evoked a sharp peak in firing rate of "ON" units followed by a very fast adaptation phase that contrasted with the slow adaptation observed in previous recordings of primary afferents. The amplitudes of this peak, the novelty detection potential, and the behavioral novelty responses, show the same dependence on the departure of the newest stimulus intensity from the weighted average of preceding ones suggesting that the signals encoded by "ON" neurons underlay the novelty detection potential, propagates through the hierarchical organization of the electromotor control, and finally contribute to accelerate the electric organ discharge rate. This suggests that detecting novelty at the very early processing stage of electrosensory signals is essential to adapt the electrosensory sampling rate to exploration requirements as they change dynamically.

Response of toadfish (Opsanus tau) utricular afferents to multimodal inputs

The inner ear of teleost fishes is composed of three paired multimodal otolithic end organs (saccule, utricle, and lagena), which encode auditory and vestibular inputs via the deflection of hair cells contained within the sensory epithelia of each organ. However, it remains unclear how the multimodal otolithic end organs of the teleost inner ear simultaneously integrate vestibular and auditory inputs. Therefore, microwire electrodes were chronically implanted using a 3D printed micromanipulator into the utricular nerve of oyster toadfish (Opsanus tau) to determine how utricular afferents respond to conspecific mate vocalizations termed boatwhistles (180 Hz fundamental frequency) during movement. Utricular afferents were recorded while fish were passively moved using a sled system along an underwater track at variable speeds (velocity: 4.0 - 12.5 cm/s; acceleration: 0.2 - 2.6 cm/s²) and while fish freely swam (velocity: 3.5 - 18.6 cm/s; acceleration: 0.8 - 29.8 cm/s²). Afferent fiber activities (spikes/s) increased in response to the onset of passive and active movements; however, afferent fibers differentially adapted to sustained movements. Additionally, utricular afferent fibers remained sensitive to playbacks of conspecific male boatwhistle vocalizations during both passive and active movements. Here, we demonstrate in alert toadfish that utricular afferents exhibit enhanced activity levels (spikes/s) in response to behaviorally-relevant acoustic stimuli during swimming.

Multiple behavior-specific cancellation signals contribute to suppressing predictable sensory reafference in a cerebellum-like structure

Movement induces sensory stimulation of an animal's own sensory receptors, termed reafference. With a few exceptions, notably vestibular and proprioception, this reafference is unwanted sensory noise and must be selectively filtered in order to detect relevant external sensory signals. In the cerebellum-like electrosensory nucleus of elasmobranch fish, an adaptive filter preserves novel signals by generating cancellation signals that suppress predictable reafference. A parallel fiber network supplies the principal Purkinje-like neurons (called ascending efferent neurons, AENs) with behavior-associated internal reference signals, including motor corollary discharge and sensory feedback, from which predictive cancellation signals are formed. How distinct behavior-specific cancellation signals interact within AENs when multiple behaviors co-occur and produce complex, changing patterns of reafference is unknown. Here, we show that when multiple streams of internal reference signals are available, cancellation signals form that are specific to parallel fiber inputs temporally correlated with, and therefore predictive of, sensory reafference. A single AEN has the capacity to form more than one cancellation signal, and AENs form multiple cancellation signals simultaneously and modify them independently during co-occurring behaviors. Cancellation signals update incrementally during continuous behaviors, as well as episodic bouts of behavior that last minutes to hours. Finally, individual AENs, independently of their neighbors, form unique AEN-specific cancellation signals that depend on the particular sensory reafferent input it receives. Together, these results demonstrate the capacity of the adaptive filter to utilize multiple cancellation signals to suppress dynamic patterns of reafference arising from complex co-occurring and intermittently performed behaviors.

A cerebellum-like circuit in the lateral line system of fish cancels mechanosensory input associated with its own movements

An animal's own movement exerts a profound impact on sensory input to its nervous system. Peripheral sensory receptors do not distinguish externally generated stimuli from stimuli generated by an animal's own behavior (reafference) - although the animal often must. One way that nervous systems can solve this problem is to provide movement-related signals (copies of motor commands and sensory feedback) to sensory systems, which can then be used to generate predictions that oppose or cancel out sensory responses to reafference. Here, we studied the use of movement-related signals to generate sensory predictions in the lateral line medial octavolateralis nucleus (MON) of the little skate. In the MON, mechanoreceptive afferents synapse on output neurons that also receive movement-related signals from central sources, via a granule cell parallel fiber system. This parallel fiber system organization is characteristic of a set of so-called cerebellum-like structures. Cerebellum-like structures have been shown to support predictive cancellation of reafference in the electrosensory systems of fish and the auditory system of mice. Here, we provide evidence that the parallel fiber system in the MON can generate predictions that are negative images of (and therefore cancel) sensory input associated with respiratory and fin movements. The MON, found in most aquatic vertebrates, is probably one of the most primitive cerebellum-like structures and a starting point for cerebellar evolution. The results of this study contribute to a growing body of work that uses an evolutionary perspective on the vertebrate cerebellum to understand its functional diversity in animal behavior.

Variability in locomotor dynamics reveals the critical role of feedback in task control

Animals vary considerably in size, shape, and physiological features across individuals, but yet achieve remarkably similar behavioral performances. We examined how animals compensate for morphophysiological variation by measuring the system dynamics of individual knifefish (Eigenmannia virescens) in a refuge tracking task. Kinematic measurements of Eigenmannia were used to generate individualized estimates of each fish’s locomotor plant and controller, revealing substantial variability between fish. To test the impact of this variability on behavioral performance, these models were used to perform simulated ‘brain transplants’—computationally swapping controllers and plants between individuals. We found that simulated closed-loop performance was robust to mismatch between plant and controller. This suggests that animals rely on feedback rather than precisely tuned neural controllers to compensate for morphophysiological variability.

People come in different shapes and sizes, but most will perform similarly well if asked to complete a task requiring fine manual dexterity – such as holding a pen or picking up a single grape. How can different individuals, with different sized hands and muscles, produce such similar movements? One explanation is that an individual’s brain and nervous system become precisely tuned to mechanics of the body’s muscles and skeleton. An alternative explanation is that brain and nervous system use a more “robust” control policy that can compensate for differences in the body by relying on feedback from the senses to guide the movements.

To distinguish between these two explanations, Uyanik et al. turned to weakly electric freshwater fish known as glass knifefish. These fish seek refuge within root systems, reed grass and among other objects in the water. They swim backwards and forwards to stay hidden despite constantly changing currents. Each fish shuttles back and forth by moving a long ribbon-like fin on the underside of its body. Uyanik et al. measured the movements of the ribbon fin under controlled conditions in the laboratory, and then used the data to create computer models of the brain and body of each fish. The models of each fish’s brain and body were quite different.

To study how the brain interacts with the body, Uyanik et al. then conducted experiments reminiscent of those described in the story of Frankenstein and transplanted the brain from each computer model into the body of different model fish. These “brain swaps” had almost no effect on the model’s simulated swimming behavior. Instead, these “Frankenfish” used sensory feedback to compensate for any mismatch between their brain and body.

This suggests that, for some behaviors, an animal’s brain does not need to be precisely tuned to the specific characteristics of its body. Instead, robust control of movement relies on many seemingly redundant systems that provide sensory feedback. This has implications for the field of robotics. It further suggests that when designing robots, engineers should prioritize enabling the robots to use sensory feedback to cope with unexpected events, a well-known idea in control engineering.

Sequence and hierarchy in vocal rhythms and phonology

I explore the neural and evolutionary origins of phonological hierarchy, building on Peter MacNeilage's frame/content model, which suggests that human speech evolved from primate nonvocal jaw oscillations, for example, lip smack displays, combined with phonation. Considerable recent data, reviewed here, support this proposition. I argue that the evolution of speech motor control required two independent components. The first, identified by MacNeilage, is the diversification of phonetic "content" within a simple sequential "frame," and would be within reach of nonhuman primates, by simply intermittently activating phonation during lip smack displays. Such voicing control requires laryngeal control, hypothesized to necessitate direct corticomotor connections to the nucleus ambiguus. The second component, proposed here, involves imposing additional hierarchical rhythmic structure upon the "flat" control sequences typifying mammalian vocal tract oscillations and is required for the flexible combinatorial capacity observed in modern phonology. I hypothesize that phonological hierarchy resulted from a marriage of a preexisting capacity for sequential structure seen in other primates, with novel hierarchical motor control circuitry (potentially evolved in tool use and/or musical contexts). In turn, this phonological hierarchy paved the way for phrasal syntactic hierarchy. I support these arguments using comparative and neural data from nonhuman primates and birdsong.

Internally Generated Predictions Enhance Neural and Behavioral Detection of Sensory Stimuli in an Electric Fish

Studies of cerebellum-like circuits in fish have demonstrated that synaptic plasticity shapes the motor corollary discharge responses of granule cells into highly-specific predictions of self-generated sensory input. However, the functional significance of such predictions, known as negative images, has not been directly tested. Here we provide evidence for improvements in neural coding and behavioral detection of prey-like stimuli due to negative images. In addition, we find that manipulating synaptic plasticity leads to specific changes in circuit output that disrupt neural coding and detection of prey-like stimuli. These results link synaptic plasticity, neural coding, and behavior and also provide a circuit-level account of how combining external sensory input with internally generated predictions enhances sensory processing.

Lateral line sensitivity in free-swimming toadfish Opsanus tau

A longstanding question in aquatic animal sensory physiology is the impact of self-generated movement on lateral line sensitivity. One hypothesis is that efferent modulation of the sensory hair cells cancels self-generated noise and allows fish to sample their surroundings while swimming. In this study, microwire electrodes were chronically implanted into the anterior lateral line nerve of oyster toadfish and neural activity was monitored during forward movement. Fish were allowed to freely swim or were moved by a tethered sled. In all cases, neural activity increased during movement with no evidence of efferent modulation. The anterior lateral line of moving fish responded to a vibrating sphere or the tail oscillations of a robotic fish, indicating that the lateral line also remains sensitive to outside stimulus during self-generated movement. The results suggest that during normal swim speeds, lateral line neuromasts are not saturated and retain the ability to detect external stimuli without efferent modulation.

Morphological development of the dorsal hindbrain in an elasmobranch fish (Leucoraja erinacea)

The developmental anatomy of the dorsal hindbrain in an elasmobranch fish, Leucoraja erinacea, is described. We focus on the cerebellum, which is a synapomorphy for gnathostomes. Cerebellar development in L. erinacea, a representative of the most basal gnathostome lineage, may be a proxy for the ancestral state of cerebellar development. We also focus on sensory processing regions termed 'cerebellum-like' structures due to common anatomical and physiological features with the cerebellum. These structures may be considered generatively homologous if they share common developmental features. To test this hypothesis, the morphological development of the cerebellum and cerebellum-like structures must first be described. Of particular importance is the development of common features, such as the molecular layer, which is the defining characteristic of these structures. The molecular layers of the cerebellum and cerebellum-like structures are supplied with parallel fiber axons from distinct granule cell populations. These are the lateral granule mass, the dorsal granular ridge, the medial granule mass, and the granular eminences of the cerebellum. Cerebellar and cerebellar-like development in L. erinacea is similar to development in other elasmobranchs. The temporal order in which these granule cell populations develop suggests an evolutionary history of duplication or expansion of an existing developmental event.

Eye movements, sensorimotor adaptation and cerebellar-dependent learning in autism: toward potential biomarkers and subphenotypes

Because of the wide range of symptoms expressed in individuals with autism spectrum disorder (ASD) and their idiosyncratic severity, it is unlikely that a single remedial approach will be universally effective. Resolution of this dilemma requires identifying subgroups within the autism spectrum, based on symptom set and severity, on an underlying neuro-structural difference, and on specific behavioral dysfunction. This will provide critical insight into the disorder and may lead to better diagnoses, and more targeted remediation in these subphenotypes of people with ASD. In this review, we discuss findings that appear to link the structure of the cerebellar vermis and plasticity of the saccadic eye-movement system in people with an autism spectrum disorder (ASD). Differences in cerebellar vermis structure in ASD could critically impact visuo-sensorimotor development in early infancy, which may in turn manifest as the visual orienting, communication and social interaction differences often seen in this population. It may be possible to distinguish a subpopulation of children with vermal hypoplasia, to establish whether this group manifests more severe deficits in visual orienting and in adaptation to persistent visual errors, and to establish whether this putative subphenotype of ASD is associated with a specific and distinct clinical symptom profile.

A cerebellum-like circuit in the auditory system cancels responses to self-generated sounds

The dorsal cochlear nucleus (DCN) integrates auditory nerve input with a diverse array of sensory and motor signals processed within circuity similar to the cerebellum. Yet how the DCN contributes to early auditory processing has been a longstanding puzzle. Using electrophysiological recordings in mice during licking behavior we show that DCN neurons are largely unaffected by self-generated sounds while remaining sensitive to external acoustic stimuli. Recordings in deafened mice, together with neural activity manipulations, indicate that self-generated sounds are cancelled by non-auditory signals conveyed by mossy fibers. In addition, DCN neurons exhibit gradual reductions in their responses to acoustic stimuli that are temporally correlated with licking. Together, these findings suggest that DCN may act as an adaptive filter for cancelling self-generated sounds. Adaptive filtering has been established previously for cerebellum-like sensory structures in fish suggesting a conserved function for such structures across vertebrates.

Random synaptic feedback weights support error backpropagation for deep learning

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning.

A quest for excitation: Theoretical arguments and immunohistochemical evidence of excitatory granular cells in the ELL of Gnathonemus petersii

The Electrosensory Lateral Line lobe (ELL) is the first central target where the electrosensory information encoded in the spatiotemporal pattern electroreceptor afferent discharges is processed. These afferents encode the minute amplitude changes of the basal electric field through both a change in latency and discharge rate. In the ELL the time and rate-coded input pattern of the sensory periphery goes through the granular cell layer before reaching the main efferent cells of the network: large fusiform (LF) and large ganglion (LG) cells. The evidence until now shows that granular cells are inhibitory. Given that large fusiform cells are excited by the sensory input, it remains a mystery how the afferent input produce excitation through a layer composed by only inhibitory cells. We addressed this problem by modeling how the known circuitry of the ELL could produce excitation in LF cells with only inhibitory granular cells. Alternatively we show that a network composed of a mix of excitatory and inhibitory granular cell not only performs better, as expected, carrying excitation to LF cells but it does so robustly and at higher sensitivity by enhancing the contrast of the electric image between the periphery and the ELLs output. We then show with refined histological methods that a subpopulation of the granular cells indeed are excitatory, providing the necessary input for this contrast enhancing mechanism.

Mechanosensory Lateral Line Nerve Projections to Auditory Neurons in the Dorsal Descending Octaval Nucleus in the Goldfish, Carassius auratus

The nucleus medialis is the main first-order target of the mechanosensory lateral line (LL) system. This report definitively demonstrates that mechanosensory LL inputs also terminate in the ipsilateral dorsal portion of the descending octaval nucleus (dDO) in the goldfish. The dDO, which is the main first-order auditory nucleus in bony fishes, includes neurons that receive direct input from the otolithic end organs of the inner ear and project to the auditory midbrain. There are two groups of such auditory projection neurons: medial and lateral. The medial and the lateral groups in turn contain several neuronal populations, each of which includes one or more morphological cell types. In goldfish, the exclusively mechanosensory anterior and posterior LL nerves terminate only on specific cell types of auditory projection neurons in the lateral dDO group. Single neurons in the lateral dDO group may receive input from both anterior and posterior LL nerves. It is possible that some of the lateral dDO neurons that receive LL input also receive input from one or more of the otolithic end organs. These results are consistent with functional studies demonstrating low frequency acoustic sensitivity of the mechanosensory LL in teleosts, and they reveal that the anatomical substrate for sensory integration of otolithic and LL inputs is present at the origin of the central ascending auditory pathway in an otophysine fish.

Listening to another sense: somatosensory integration in the auditory system

Conventionally, sensory systems are viewed as separate entities, each with its own physiological process serving a different purpose. However, many functions require integrative inputs from multiple sensory systems and sensory intersection and convergence occur throughout the central nervous system. The neural processes for hearing perception undergo significant modulation by the two other major sensory systems, vision and somatosensation. This synthesis occurs at every level of the ascending auditory pathway: the cochlear nucleus, inferior colliculus, medial geniculate body and the auditory cortex. In this review, we explore the process of multisensory integration from (1) anatomical (inputs and connections), (2) physiological (cellular responses), (3) functional and (4) pathological aspects. We focus on the convergence between auditory and somatosensory inputs in each ascending auditory station. This review highlights the intricacy of sensory processing and offers a multisensory perspective regarding the understanding of sensory disorders.

Consensus paper: the role of the cerebellum in perceptual processes

Various lines of evidence accumulated over the past 30 years indicate that the cerebellum, long recognized as essential for motor control, also has considerable influence on perceptual processes. In this paper, we bring together experts from psychology and neuroscience, with the aim of providing a succinct but comprehensive overview of key findings related to the involvement of the cerebellum in sensory perception. The contributions cover such topics as anatomical and functional connectivity, evolutionary and comparative perspectives, visual and auditory processing, biological motion perception, nociception, self-motion, timing, predictive processing, and perceptual sequencing. While no single explanation has yet emerged concerning the role of the cerebellum in perceptual processes, this consensus paper summarizes the impressive empirical evidence on this problem and highlights diversities as well as commonalities between existing hypotheses. In addition to work with healthy individuals and patients with cerebellar disorders, it is also apparent that several neurological conditions in which perceptual disturbances occur, including autism and schizophrenia, are associated with cerebellar pathology. A better understanding of the involvement of the cerebellum in perceptual processes will thus likely be important for identifying and treating perceptual deficits that may at present go unnoticed and untreated. This paper provides a useful framework for further debate and empirical investigations into the influence of the cerebellum on sensory perception.

Tinnitus

Tinnitus, the perception of sound in the absence of an external sound, usually results from a disorder of: (1) the auditory system (usually peripheral, rarely central); (2) the somatosensory system (head and neck); or (3) a combination of the two. Its cause can be determined through its characteristics. The history must include the tinnitus': (1) quality (including whether it can ever be pulsatile or have a clicking component); (2) location; (3) variability; (4) predominant pitch (low or high); and (5) whether the patient can do something to modulate the percept. In addition to the standard neuro-otologic examination, the exam should include inspection of the teeth for evidence of wear, listening around the ear and neck for sounds similar to the tinnitus, palpation of the craniocervical musculature for trigger points, and probing whether the tinnitus percept can be modulated with "somatic testing." All subjects should have a recent audiogram. Presently the most compelling tinnitus theory is the dorsal cochlear nucleus (DCN) hypothesis: both the auditory and somatosensory systems converge upon and interact within the DCN. If the activity of the DCN's somatosensory-interacting fusiform cells exceeds an individual's tinnitus threshold, then tinnitus results.

Directional sound sensitivity in utricular afferents in the toadfish, Opsanus tau

The inner ear of fishes contains three paired otolithic endorgans, the saccule, lagena, and utricle, which function as biological accelerometers. The saccule is the largest otolithin most fishes and much of our current understanding on auditory function in this diverse group of vertebrates is derived from anatomical and neurophysiological studies on this endorgan. In contrast, less is known about how the utricle contributes to auditory functions. Chronically implanted electrodes were used, along with neural telemetry or tethers to record primary afferent responses from the utricular nerve in free-ranging and naturally behaving oyster toadfish Opsanus tau Linnaeus. The hypothesis was that the utricle plays a role in detecting underwater sounds, including conspecific vocalizations, and exhibits directional sensitivity. Utricular afferents responded best to low frequency (80-200 Hz) pure tones and to playbacks of conspecific boatwhistles and grunts (80 to 180 Hz fundamental frequency), with the majority of the units (∼75%) displaying a clear, directional response, which may allow the utricle to contribute to sound detection and localization during social interactions. Responses were well within the sound intensity levels of toadfish vocalization (approximately 140 SPL dBrms re: 1µPa with fibers sensitive to thresholds of approximately 120 SPL dBrms re: 1µPa). Neurons were also stimulated by self-generated body movements such as opercular movements and swimming. This study is the first to investigate underwater sound-evoked response properties of primary afferents from the utricle of an unrestrained/unanesthetized free-swimming teleost fish. These data provide experimental evidence that the utricle has an auditory function, and can contribute to directional hearing to facilitate sound localization.

Network plasticity in adaptive filtering and behavioral habituation

The ability of organisms to seamlessly ignore familiar, inconsequential stimuli improves their selective attention and response to salient features of the environment. Here, I propose that this fundamental but unexplained phenomenon substantially derives from the ability of any pattern of neural excitation to create an enhanced inhibitory (or "negative") image of itself through target-specific scaling of inhibitory inputs onto active excitatory neurons. Familiar stimuli encounter strong negative images and are therefore less likely to be transmitted to higher brain centers. Integrating historical and recent observations, the negative-image model described here provides a mechanistic framework for understanding habituation, which is connected to ideas on dynamic predictive coding. In addition, it suggests insights for understanding autism spectrum disorders.

Supervised learning with complex spikes and spike-timing-dependent plasticity

One distinctive feature of Purkinje cells is that they have two types of discharge: in addition to simple spikes they fire complex spikes in response to input from the climbing fibers. These complex spikes have an initial rapid burst of spikes and spikelets followed by a sustained depolarization; in some models of cerebellar function this climbing fiber input supervises learning in Purkinje cells. On the other hand, synaptic plasticity is often thought to rely on the timing of pre-synaptic and post-synaptic spikes. It is suggested here that the period of depolarization following a complex spike, combined with a simple spike-timing-dependent plasticity rule, gives a mechanism for the climbing fiber to supervise learning in the Purkinje cell. This proposal is illustrated using a simple simulation in which it is seen that the climbing fiber succeeds in supervising the learning.

Decorrelation learning in the cerebellum: computational analysis and experimental questions

Many cerebellar models use a form of synaptic plasticity that implements decorrelation learning. Parallel fibers carrying signals positively correlated with climbing-fiber input have their synapses weakened (long-term depression), whereas those carrying signals negatively correlated with climbing input have their synapses strengthened (long-term potentiation). Learning therefore ceases when all parallel-fiber signals have been decorrelated from climbing-fiber input. This is a computationally powerful rule for supervised learning and can be cast in a spike-timing dependent plasticity form for comparison with experimental evidence. Decorrelation learning is particularly well suited to sensory prediction, for example, in the reafference problem where external sensory signals are interfered with by reafferent signals from the organism's own movements, and the required circuit appears similar to the one found to mediate classical eye blink conditioning. However, for certain stimuli, avoidance is a much better option than simple prediction, and decorrelation learning can also be used to acquire appropriate avoidance movements. One example of a stimulus to be avoided is retinal slip that degrades visual processing, and decorrelation learning appears to play a role in the vestibulo-ocular reflex that stabilizes gaze in the face of unpredicted head movements. Decorrelation learning is thus suitable for both sensory prediction and motor control. It may also be well suited for generic spatial and temporal coordination, because of its ability to remove the unwanted side effects of movement. Finally, because it can be used with any kind of time-varying signal, the cerebellum could play a role in cognitive processing.

What does motor efference copy represent? Evidence from speech production

How precisely does the brain predict the sensory consequences of our actions? Efference copy is thought to reflect the predicted sensation of self-produced motor acts, such as the auditory feedback heard while speaking. Here, we use magnetoencephalographic imaging (MEG-I) in human speakers to demonstrate that efference copy prediction does not track movement variability across repetitions of the same motor task. Specifically, spoken vowels were less accurately predicted when they were less similar to a speaker's median production, even though the prediction is thought to be based on the very motor commands that generate each vowel. Auditory cortical responses to less prototypical speech productions were less suppressed, resembling responses to speech errors, and were correlated with later corrective movement, suggesting that the suppression may be functionally significant for error correction. The failure of the motor system to accurately predict less prototypical speech productions suggests that the efferent-driven suppression does not reflect a sensory prediction, but a sensory goal.

Learning contrast-invariant cancellation of redundant signals in neural systems

Cancellation of redundant information is a highly desirable feature of sensory systems, since it would potentially lead to a more efficient detection of novel information. However, biologically plausible mechanisms responsible for such selective cancellation, and especially those robust to realistic variations in the intensity of the redundant signals, are mostly unknown. In this work, we study, via in vivo experimental recordings and computational models, the behavior of a cerebellar-like circuit in the weakly electric fish which is known to perform cancellation of redundant stimuli. We experimentally observe contrast invariance in the cancellation of spatially and temporally redundant stimuli in such a system. Our model, which incorporates heterogeneously-delayed feedback, bursting dynamics and burst-induced STDP, is in agreement with our in vivo observations. In addition, the model gives insight on the activity of granule cells and parallel fibers involved in the feedback pathway, and provides a strong prediction on the parallel fiber potentiation time scale. Finally, our model predicts the existence of an optimal learning contrast around 15% contrast levels, which are commonly experienced by interacting fish.

Linking oscillations in cerebellar circuits

In many neuroscience fields, the study of local and global rhythmicity has been receiving increasing attention. These network influences could directly impact on how neuronal groups interact together, organizing for different contexts. The cerebellar cortex harbors a variety of such local circuit rhythms, from the rhythms in the cerebellar cortex per se, or those dictated from important afferents. We present here certain cerebellar oscillatory phenomena that have been recorded in rodents and primates. Those take place in a range of frequencies: from the more known oscillations in the 4-25 Hz band, such as the olivocerebellar oscillatory activity and the granule cell layer oscillations, to the more recently reported slow (<1 Hz oscillations), and the fast (>150 Hz) activity in the Purkinje cell layer. Many of these oscillations appear spontaneously in the circuits, and are modulated by behavioral imperatives. We review here how those oscillations are recorded, some of their modulatory mechanisms, and also identify some of the cerebellar nodes where they could interact. A particular emphasis has been placed on how these oscillations could be modulated by movement and certain neuropathological manifestations. Many of those oscillations could have a definite impact on the way information is processed in the cerebellum and how it interacts with other structures in a variety of contexts.

Stimulus-timing dependent multisensory plasticity in the guinea pig dorsal cochlear nucleus

Multisensory neurons in the dorsal cochlear nucleus (DCN) show long-lasting enhancement or suppression of sound-evoked responses when stimulated with combined somatosensory-auditory stimulation. By varying the intervals between sound and somatosensory stimuli we show for the first time in vivo that DCN bimodal responses are influenced by stimulus-timing dependent plasticity. The timing rules and time courses of the observed stimulus-timing dependent plasticity closely mimic those of spike-timing dependent plasticity that have been demonstrated in vitro at parallel-fiber synapses onto DCN principal cells. Furthermore, the degree of inhibition in a neuron influences whether that neuron has Hebbian or anti-Hebbian timing rules. As demonstrated in other cerebellar-like circuits, anti-Hebbian timing rules reflect adaptive filtering, which in the DCN would result in suppression of sound-evoked responses that are predicted by activation of somatosensory inputs, leading to the suppression of body-generated signals such as self-vocalization.

Parallel processing of environmental recognition and locomotion in the mouse striatum

Information processing in behaving animals has been the target of many studies in the striatum; however, its dynamics and complexity remain to a large extent unknown. Here, we chronically recorded neuronal populations in dorsal striatum as mice were exposed to a novel environment, a paradigm which enables the dissociation of locomotion and environmental recognition. The findings indicate that non-overlapping populations of striatal projection neurons-the medium spiny neurons-reliably encode locomotion and environmental identity, whereas two subpopulations of short-spike interneurons encode distinct information: the fast spiking interneurons preferentially encode locomotion whereas the second type of interneurons preferentially encodes environmental identity. The three neuronal subgroups used cell-type specific coding schemes. This study provides evidence for the existence of parallel processing circuits within the sensorimotor region of the striatum.

Human cortical sensorimotor network underlying feedback control of vocal pitch

The control of vocalization is critically dependent on auditory feedback. Here, we determined the human peri-Sylvian speech network that mediates feedback control of pitch using direct cortical recordings. Subjects phonated while a real-time signal processor briefly perturbed their output pitch (speak condition). Subjects later heard the same recordings of their auditory feedback (listen condition). In posterior superior temporal gyrus, a proportion of sites had suppressed responses to normal feedback, whereas other spatially independent sites had enhanced responses to altered feedback. Behaviorally, speakers compensated for perturbations by changing their pitch. Single-trial analyses revealed that compensatory vocal changes were predicted by the magnitude of both auditory and subsequent ventral premotor responses to perturbations. Furthermore, sites whose responses to perturbation were enhanced in the speaking condition exhibited stronger correlations with behavior. This sensorimotor cortical network appears to underlie auditory feedback-based control of vocal pitch in humans.

Responses of somatosensory area 2 neurons to actively and passively generated limb movements

Control of reaching movements requires an accurate estimate of the state of the limb, yet sensory signals are inherently noisy, because of both noise at the receptors themselves and the stochastic nature of the information representation by neural discharge. One way to derive an accurate representation from noisy sensor data is to combine it with the output of a forward model that considers both the previous state estimate and the noisy input. We recorded from primary somatosensory cortex (S1) in macaques (Macaca mulatta) during both active and passive movements to investigate how the proprioceptive representation of movement in S1 may be modified by the motor command (through efference copy). We found neurons in S1 that respond to one or both movement types covering a broad distribution from active movement only, to both, to passive movement only. Those neurons that responded to both active and passive movements responded with similar directional tuning. Confirming earlier results, some, but not all, neurons responded before the onset of volitional movements, possibly as a result of efference copy. Consequently, many of the features necessary to combine the forward model with proprioceptive feedback appear to be present in S1. These features would not be expected from combinations of afferent receptor responses alone.

Adaptive filters and internal models: multilevel description of cerebellar function

Cerebellar function is increasingly discussed in terms of engineering schemes for motor control and signal processing that involve internal models. To address the relation between the cerebellum and internal models, we adopt the chip metaphor that has been used to represent the combination of a homogeneous cerebellar cortical microcircuit with individual microzones having unique external connections. This metaphor indicates that identifying the function of a particular cerebellar chip requires knowledge of both the general microcircuit algorithm and the chip's individual connections. Here we use a popular candidate algorithm as embodied in the adaptive filter, which learns to decorrelate its inputs from a reference ('teaching', 'error') signal. This algorithm is computationally powerful enough to be used in a very wide variety of engineering applications. However, the crucial issue is whether the external connectivity required by such applications can be implemented biologically. We argue that some applications appear to be in principle biologically implausible: these include the Smith predictor and Kalman filter (for state estimation), and the feedback-error-learning scheme for adaptive inverse control. However, even for plausible schemes, such as forward models for noise cancellation and novelty-detection, and the recurrent architecture for adaptive inverse control, there is unlikely to be a simple mapping between microzone function and internal model structure. This initial analysis suggests that cerebellar involvement in particular behaviours is therefore unlikely to have a neat classification into categories such as 'forward model'. It is more likely that cerebellar microzones learn a task-specific adaptive-filter operation which combines a number of signal-processing roles.

The cerebellum and cerebellum-like structures of cartilaginous fishes

The cerebellum is well developed in cartilaginous fishes, with the same cell types (barring basket cells) and organizational features found in other vertebrate groups, including mammals. In particular, the lattice-like organization of cerebellar cortex (with a molecular layer of parallel fibers, interneurons, spiny Purkinje cell dendrites, and climbing fibers) is a defining characteristic. In addition to the cerebellum, cartilaginous fishes have cerebellum-like structures in the dorsolateral wall of the hindbrain. These structures are adjacent to and, in part, contiguous with the cerebellum. They are cerebellum-like in that they have a molecular layer of parallel fibers and inhibitory interneurons that has striking organizational similarities to the molecular layer of the cerebellar cortex. However, these structures also have characteristics that differ from the cerebellum. For example, cerebellum-like structures do not have climbing fibers and are clearly sensory. They receive direct afferent input from peripheral sensory receptors and relay their outputs to midbrain sensory areas. As a consequence of this close sensory association and the ability of researchers to characterize signal processing in these structures in a behaviorally relevant context, good progress has been made in determining the fundamental processing algorithm of the cerebellum-like structures. This algorithm enables the molecular layer to act as an adaptive filter that cancels self-generated noise in electrosensory and lateral line systems. Given the fundamental similarities of the molecular layer across these structures and the phylogeny of these structures across basal vertebrates, it is clear that these structures share a common genetic-developmental program. Syngeny is a term that has been used to describe similarity of structure due to a shared genetic-developmental program, whether the structures are phylogenetically homologous or not. Given that the cerebellum and cerebellum-like structures are physically adjacent, we propose that cerebellum-like structures were the evolutionary antecedent of the cerebellum and that the cerebellum arose through a change in the genetic-developmental program, amounting to a duplication of existing structure. Such duplication to form adjacent structures can be considered a special case of syngeny. On this view, the cerebellum is an evolutionary innovation in gnathostomes that is literally superimposed on pre-existing underlying brain structures and pathways. From this perspective, the cerebellum can be considered an example of 'subsumption architecture', a term that describes the addition of modules that add computational power while maintaining existing fundamental functionality. This addition is reflected in the finding that in elasmobranchs with relatively large brains, the size of the telencephalon and cerebellum enlarge disproportionately, while those parts of the brain that contain more direct sensory and motor connections do not. Added 'computational' power in the chondrichthyan brain and the comparative function and evolution of the cerebellum and cerebellum-like structures across the cartilaginous fishes supports the idea of the cerebellum as an example of subsumption architecture.

An internal model architecture for novelty detection: implications for cerebellar and collicular roles in sensory processing

The cerebellum is thought to implement internal models for sensory prediction, but details of the underlying circuitry are currently obscure. We therefore investigated a specific example of internal-model based sensory prediction, namely detection of whisker contacts during whisking. Inputs from the vibrissae in rats can be affected by signals generated by whisker movement, a phenomenon also observable in whisking robots. Robot novelty-detection can be improved by adaptive noise-cancellation, in which an adaptive filter learns a forward model of the whisker plant that allows the sensory effects of whisking to be predicted and thus subtracted from the noisy sensory input. However, the forward model only uses information from an efference copy of the whisking commands. Here we show that the addition of sensory information from the whiskers allows the adaptive filter to learn a more complex internal model that performs more robustly than the forward model, particularly when the whisking-induced interference has a periodic structure. We then propose a neural equivalent of the circuitry required for adaptive novelty-detection in the robot, in which the role of the adaptive filter is carried out by the cerebellum, with the comparison of its output (an estimate of the self-induced interference) and the original vibrissal signal occurring in the superior colliculus, a structure noted for its central role in novelty detection. This proposal makes a specific prediction concerning the whisker-related functions of a region in cerebellar cortical zone A₂ that in rats receives climbing fibre input from the superior colliculus (via the inferior olive). This region has not been observed in non-whisking animals such as cats and primates, and its functional role in vibrissal processing has hitherto remained mysterious. Further investigation of this system may throw light on how cerebellar-based internal models could be used in broader sensory, motor and cognitive contexts.

Otolith end organ projections to auditory neurons in the descending octaval nucleus of the goldfish, Carassius auratus: a confocal analysis

The distribution of axons from the saccule, lagena, and utricle to descending octaval nucleus neurons that project to the auditory midbrain in the goldfish is reported. We have divided these auditory projection neurons, located in the dorsal portion of the descending octaval nucleus (dDO), into two groups, medial and lateral, each of which contains several neuronal populations based on morphology and location. At most levels of the dDO, there are three medial and three lateral populations; the rostral dDO contains an additional lateral population. The saccule provides input to each of the seven medial and lateral populations but appears to be the exclusive/nearly exclusive source of primary input to the most dorsal cell group of the medial population. Along with the saccule, the lagena and utricle each supply the remaining six medial and lateral populations. Neurons in each of these populations receive input from more than one end organ. One medial and one lateral population include neurons that receive remarkably large contacts from utricular afferents. Overall, the results reveal a more substantial input from the lagena and utricle to the main first-order auditory nucleus in the goldfish than was previously recognized, suggest this nucleus is composed of functionally distinct populations, and relate to functional and evolutionary issues about hearing in early vertebrates.

Identifying self- and nonself-generated signals: lessons from electrosensory systems

This chapter provides a short review of the mechanisms used by electroreceptive fish to discriminate self- from nonself-generated signals. Electroreception is used by animals to detect objects of electric impedance different from the water, to detect natural electrogenic sources and to communicate signals between conspecifics. Electroreceptive animals may generate electric fields either with the purpose of electrically illuminating the neighborhood or as an epiphenomenon of other functions. In addition, the presence of the fish body as a conductive object in a scene funnels the current flow and, consequently, animal movements also generate signals by changing the body shape or the spatial relationship of the body with the surrounding objects. Therefore, mechanisms for discrimination between self and externally generated signals are very important for constructing a coherent representation of the environment. Some mechanisms facilitate and stream the flow of signals carried by the self-generated electric field. Others are designed to reject unwanted interference coming from self-generated movements or even the self-generated electric field. Finally, more complex operations involving sensory motor integration are used for discriminating between self- and conspecific- generated communication signals. Despite the evolutionary distance between animals endowed with electric sense, mechanisms for self-identification reappear with few differences between species. This suggests that many of the possible strategies are present in vertebrates may be found in these fish. Therefore, we have much to learn about self recognition from the study of electroreception.